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On Mar 27, 2014, at 5:10 PM, Joshua Harlow <harlowja at yahoo-inc.com> wrote:

> Thanks for the description!
> 
> The steps here seem very much like what a taskflow engine does (which is good).
> 
> To connect this to how I think could work in taskflow.
> Someone creates tasks/flows describing the work to-be-done (converting a DSL -> taskflow tasks/flows/retry[1] objects…)
> On execute(workflow) engine creates a new workflow execution, computes the first batch of tasks, creates executor for those tasks (remote, local…) and executes those tasks.
> Waits for response back from futures returned from executor.
> Receives futures responses (or receives new response DELAY, for example), or exceptions…
> Continues sending out batches of tasks that can be still be executing (aka tasks that don't have dependency on output of delayed tasks).
> If any delayed tasks after repeating #2-5 as many times as it can, the engine will shut itself down (see http://tinyurl.com/l3x3rrb).
Why would engine treat long running tasks differently? The model Mistral tried out is the engine sends the batch of tasks and goes asleep; the 'worker/executor' is calling engine back when the task(s) complete. Can it be applied 
> On delay task finishing some API/webhook/other (the mechanism imho shouldn't be tied to webhooks, at least not in taskflow, but should be left up to the user of taskflow to decide how to accomplish this) will be/must be responsible for resuming the engine and setting the result for the previous delayed task.
Oh no, webhook is the way to expose it to 3rd party system. From the library standpoint it's just an API call. 

One can do it even now by getting the appropriate Flow_details, instantiating and engine (flow, flow_details) and running it to continue from where it left out. Is it how you mean it? But I keep on dreaming of a passive version of TaskFlow engine which treats all tasks the same and exposes one extra method - handle_tasks. 
> Repeat 2 -> 7 until all tasks have executed/failed.
> Profit!

> This seems like it could be accomplished, although there are race conditions in the #6 (what if multiple delayed requests are received at the same time)? What locking is done to ensure that this doesn't cause conflicts?
Engine must handle concurrent calls of mutation methods - start, stop, handle_action. How -  differs depending on engine running in multiple threads or in event loop on queues of calls. 

> Does the POC solve that part (no simultaneous step #5 from below)?
Yes although we may want to revisit the current solution. 

> There was a mention of a watch-dog (ideally to ensure that delayed tasks can't just sit around forever), was that implemented?
If _delayed_ tasks and 'normal' tasks are treat alike, this is just a matter of timeout as a generic property on a task. So Mistral didn't have to have it. For the proposal above, a separate treatment is necessary for _delayed_ tasks. 
> 
> [1] https://wiki.openstack.org/wiki/TaskFlow#Retries (new feature!)
This is nice. I would call it a 'repeater': running a sub flow several times with various data for various reasons is reacher then 'retry'. 
What about the 'retry policy' on individual task? 

> 
> From: Dmitri Zimine <dz at stackstorm.com>
> Reply-To: "OpenStack Development Mailing List (not for usage questions)" <openstack-dev at lists.openstack.org>
> Date: Thursday, March 27, 2014 at 4:43 PM
> To: "OpenStack Development Mailing List (not for usage questions)" <openstack-dev at lists.openstack.org>
> Subject: [openstack-dev] [Mistral] How Mistral handling long running delegate tasks
> 
>> Following up on http://tinyurl.com/l8gtmsw and http://tinyurl.com/n3v9lt8: this explains how Mistral handles long running delegate tasks. Note that a 'passive' workflow engine can handle both normal tasks and delegates the same way. I'll also put that on ActionDesign wiki, after discussion.
>> 
>> Diagram: 
>> https://docs.google.com/a/stackstorm.com/drawings/d/147_EpdatpN_sOLQ0LS07SWhaC3N85c95TkKMAeQ_a4c/edit?usp=sharing
>> 
>> 1. On start(workflow), engine creates a new workflow execution, computes the first batch of tasks, sends them to ActionRunner [1].
>> 2. ActionRunner creates an action and calls action.run(input)
>> 3. Action does the work (compute (10!)), produce the results,  and return the results to executor. If it returns, status=SUCCESS. If it fails it throws exception, status=ERROR.
>> 4. ActionRunner notifies Engine that the task is complete task_done(execution, task, status, results)[2]
>> 5. Engine computes the next task(s) ready to trigger, according to control flow and data flow, and sends them to ActionRunner.
>> 6. Like step 2: ActionRunner calls the action's run(input)
>> 7. A delegate action doesn't produce results: it calls out the 3rd party system, which is expected to make a callback to a workflow service with the results. It returns to ActionRunner without results, "immediately".  
>> 8. ActionRunner marks status=RUNNING [?]
>> 9. 3rd party system takes 'long time' == longer then any system component can be assumed to stay alive. 
>> 10. 3rd party component calls Mistral WebHook which resolves to engine.task_complete(workbook, id, status, results)  
>> 
>> Comments: 
>> * One Engine handles multiple executions of multiple workflows. It exposes two main operations: start(workflow) and task_complete(execution, task, status, results), and responsible for defining the next batch of tasks based on control flow and data flow. Engine is passive - it runs in a hosts' thread. Engine and ActionRunner communicate via task queues asynchronously, for details, see  https://wiki.openstack.org/wiki/Mistral/POC 
>> 
>> * Engine doesn't distinct sync and async actions, it doesn't deal with Actions at all. It only reacts to task completions, handling the results, updating the state, and queuing next set of tasks.
>> 
>> * Only Action can know and define if it is a delegate or not. Some protocol required to let ActionRunner know that the action is not returning the results immediately. A convention of returning None may be sufficient. 
>> 
>> * Mistral exposes  engine.task_done in the REST API so 3rd party systems can call a web hook.
>> 
>> DZ.
>> 
>> [1]  I use ActionRunner instead of Executor (current name) to avoid confusion: it is Engine which is responsible for executions, and ActionRunner only runs actions. We should rename it in the code.
>> 
>> [2] I use task_done for briefly and out of pure spite, in the code it is conveny_task_results.

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